Organization of response areas in ferret primary auditory cortex. Shamma, S., Fleshman, J., Wiser, P., & Versnel, H J Neurophysiol, 69(2):367-83, 1993. abstract bibtex 1. We studied the topographic organization of the response areas obtained from single- and multiunit recordings along the isofrequency planes of the primary auditory cortex in the barbiturate-anesthetized ferret. 2. Using a two-tone stimulus, we determined the excitatory and inhibitory portions of the response areas and then parameterized them in terms of an asymmetry index. The index measures the balance of excitatory and inhibitory influences around the best frequency (BF). 3. The sensitivity of responses to the direction of a frequency-modulated (FM) tone was tested and found to correlate strongly with the asymmetry index of the response areas. Specifically, cells with strong inhibition from frequencies above the BF preferred upward sweeps, and those from frequencies below the BF preferred downward sweeps. 4. Responses to spectrally shaped noise were also consistent with the asymmetry of the response areas. For instance, cells that were strongly inhibited by frequencies higher than the BF responded best to stimuli that contained least spectral energy above the BF, i.e., stimuli with the opposite asymmetry. 5. Columnar organization of the response area types was demonstrated in 66 single units from 16 penetrations. Consistent with this finding, it was also shown that response area asymmetry measured from recordings of a cluster of cells corresponded closely with those measured from its single-unit constituents. Thus, in a local region, most cells exhibited similar response area types and other response features, e.g., FM directional sensitivity. 6. The distribution of the asymmetry index values along the isofrequency planes revealed systematic changes in the symmetry of the response areas. At the center, response areas with narrow and symmetric inhibitory sidebands predominated. These gave way to asymmetric inhibition, with high-frequency inhibition (relative to the BF) becoming more effective caudally and low-frequency inhibition more effective rostrally. These response types tended to cluster along repeated bands that paralleled the tonotopic axis. 7. Response features that correlated with the response area types were also mapped along the isofrequency planes. Thus, in four animals, a map of FM directional sensitivity was shown to be superimposed on the response area map. Similarly, it was demonstrated in six animals that the spectral gradient of the most effective noise stimulus varied systematically along the isofrequency planes. 8. One functional implication of the response area organization is that cortical responses encode the locally averaged gradient of the acoustic spectrum by their differential distribution along the isofrequency planes. This enhances the representation of such features as the symmetry of spectral peaks and edges and the spectral envelope.(ABSTRACT TRUNCATED AT 400 WORDS)
@Article{Shamma1993,
author = {SA Shamma and JW Fleshman and PR Wiser and H Versnel},
journal = {J Neurophysiol},
title = {Organization of response areas in ferret primary auditory cortex.},
year = {1993},
number = {2},
pages = {367-83},
volume = {69},
abstract = {1. We studied the topographic organization of the response areas obtained
from single- and multiunit recordings along the isofrequency planes
of the primary auditory cortex in the barbiturate-anesthetized ferret.
2. Using a two-tone stimulus, we determined the excitatory and inhibitory
portions of the response areas and then parameterized them in terms
of an asymmetry index. The index measures the balance of excitatory
and inhibitory influences around the best frequency (BF). 3. The
sensitivity of responses to the direction of a frequency-modulated
(FM) tone was tested and found to correlate strongly with the asymmetry
index of the response areas. Specifically, cells with strong inhibition
from frequencies above the BF preferred upward sweeps, and those
from frequencies below the BF preferred downward sweeps. 4. Responses
to spectrally shaped noise were also consistent with the asymmetry
of the response areas. For instance, cells that were strongly inhibited
by frequencies higher than the BF responded best to stimuli that
contained least spectral energy above the BF, i.e., stimuli with
the opposite asymmetry. 5. Columnar organization of the response
area types was demonstrated in 66 single units from 16 penetrations.
Consistent with this finding, it was also shown that response area
asymmetry measured from recordings of a cluster of cells corresponded
closely with those measured from its single-unit constituents. Thus,
in a local region, most cells exhibited similar response area types
and other response features, e.g., FM directional sensitivity. 6.
The distribution of the asymmetry index values along the isofrequency
planes revealed systematic changes in the symmetry of the response
areas. At the center, response areas with narrow and symmetric inhibitory
sidebands predominated. These gave way to asymmetric inhibition,
with high-frequency inhibition (relative to the BF) becoming more
effective caudally and low-frequency inhibition more effective rostrally.
These response types tended to cluster along repeated bands that
paralleled the tonotopic axis. 7. Response features that correlated
with the response area types were also mapped along the isofrequency
planes. Thus, in four animals, a map of FM directional sensitivity
was shown to be superimposed on the response area map. Similarly,
it was demonstrated in six animals that the spectral gradient of
the most effective noise stimulus varied systematically along the
isofrequency planes. 8. One functional implication of the response
area organization is that cortical responses encode the locally averaged
gradient of the acoustic spectrum by their differential distribution
along the isofrequency planes. This enhances the representation of
such features as the symmetry of spectral peaks and edges and the
spectral envelope.(ABSTRACT TRUNCATED AT 400 WORDS)},
keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, Association Learning, Child Psychology, Habituation (Psychophysiology), Probability Theory, Analysis of Variance, Semantics, Symbolism, Behavior, Eye Movements, Macaca mulatta, Prefrontal Cortex, Cats, Dogs, Haplorhini, Photic Stimulation, Electroencephalography, Nervous System Physiology, Darkness, Grasshoppers, Light, Membrane Potentials, Neural Inhibition, Afferent, Picrotoxin, Vision, Deoxyglucose, Injections, Microspheres, Neural Pathways, Rhodamines, Choice Behavior, Speech Perception, Verbal Learning, Dominance, Cerebral, Fixation, Ocular, Language Tests, Random Allocation, Comparative Study, Saguinus, Sound Spectrography, Species Specificity, Audiometry, Auditory Threshold, Calibration, Data Interpretation, Statistical, Anesthesia, General, Electrodes, Implanted, Pitch Perception, Sound Localization, Paired-Associate Learning, Serial Learning, Auditory, Age Factors, Motion Perception, Brain Injuries, Computer Simulation, Blindness, Psychomotor Performance, Color Perception, Signal Detection (Psychology), Judgment, ROC Curve, Regression Analysis, Music, Probability, Arm, Cerebrovascular Disorders, Hemiplegia, Movement, Muscle, Skeletal, Myoclonus, Robotics, Magnetoencephalography, Phonetics, Software, Speech Production Measurement, Epilepsies, Partial, Laterality, Stereotaxic Techniques, Germany, Speech Acoustics, Verbal Behavior, Child Development, Instinct, Brain Stem, Coma, Diagnosis, Differential, Hearing Disorders, Hearing Loss, Central, Neuroma, Acoustic, Dendrites, Down-Regulation, Patch-Clamp Techniques, Wistar, Up-Regulation, Aged, Aphasia, Middle Aged, Cones (Retina), Primates, Retina, Retinal Ganglion Cells, Tympanic Membrane, Cell Communication, Extremities, Biological, Motor Activity, Rana catesbeiana, Spinal Cord, Central Nervous System, Motion, Motor Cortex, Intelligence, Macaca fascicularis, Adoption, Critical Period (Psychology), France, Korea, Magnetic Resonance Imaging, Multilingualism, Auditory Pathways, Cochlear Nerve, Loudness Perception, Neural Conduction, Sensory Thresholds, Sound, Language Disorders, Preschool, Generalization (Psychology), Vocabulary, Biophysics, Nerve Net, Potassium Channels, Sodium Channels, Cues, Differential Threshold, Arousal, Newborn, Sucking Behavior, Ferrets, Microelectrodes, 8459273},
}
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{"_id":"D8dq29zgXaCats67H","bibbaseid":"shamma-fleshman-wiser-versnel-organizationofresponseareasinferretprimaryauditorycortex-1993","author_short":["Shamma, S.","Fleshman, J.","Wiser, P.","Versnel, H"],"bibdata":{"bibtype":"article","type":"article","author":[{"firstnames":["SA"],"propositions":[],"lastnames":["Shamma"],"suffixes":[]},{"firstnames":["JW"],"propositions":[],"lastnames":["Fleshman"],"suffixes":[]},{"firstnames":["PR"],"propositions":[],"lastnames":["Wiser"],"suffixes":[]},{"firstnames":["H"],"propositions":[],"lastnames":["Versnel"],"suffixes":[]}],"journal":"J Neurophysiol","title":"Organization of response areas in ferret primary auditory cortex.","year":"1993","number":"2","pages":"367-83","volume":"69","abstract":"1. We studied the topographic organization of the response areas obtained from single- and multiunit recordings along the isofrequency planes of the primary auditory cortex in the barbiturate-anesthetized ferret. 2. Using a two-tone stimulus, we determined the excitatory and inhibitory portions of the response areas and then parameterized them in terms of an asymmetry index. The index measures the balance of excitatory and inhibitory influences around the best frequency (BF). 3. The sensitivity of responses to the direction of a frequency-modulated (FM) tone was tested and found to correlate strongly with the asymmetry index of the response areas. Specifically, cells with strong inhibition from frequencies above the BF preferred upward sweeps, and those from frequencies below the BF preferred downward sweeps. 4. Responses to spectrally shaped noise were also consistent with the asymmetry of the response areas. For instance, cells that were strongly inhibited by frequencies higher than the BF responded best to stimuli that contained least spectral energy above the BF, i.e., stimuli with the opposite asymmetry. 5. Columnar organization of the response area types was demonstrated in 66 single units from 16 penetrations. Consistent with this finding, it was also shown that response area asymmetry measured from recordings of a cluster of cells corresponded closely with those measured from its single-unit constituents. Thus, in a local region, most cells exhibited similar response area types and other response features, e.g., FM directional sensitivity. 6. The distribution of the asymmetry index values along the isofrequency planes revealed systematic changes in the symmetry of the response areas. At the center, response areas with narrow and symmetric inhibitory sidebands predominated. These gave way to asymmetric inhibition, with high-frequency inhibition (relative to the BF) becoming more effective caudally and low-frequency inhibition more effective rostrally. These response types tended to cluster along repeated bands that paralleled the tonotopic axis. 7. Response features that correlated with the response area types were also mapped along the isofrequency planes. Thus, in four animals, a map of FM directional sensitivity was shown to be superimposed on the response area map. Similarly, it was demonstrated in six animals that the spectral gradient of the most effective noise stimulus varied systematically along the isofrequency planes. 8. One functional implication of the response area organization is that cortical responses encode the locally averaged gradient of the acoustic spectrum by their differential distribution along the isofrequency planes. This enhances the representation of such features as the symmetry of spectral peaks and edges and the spectral envelope.(ABSTRACT TRUNCATED AT 400 WORDS)","keywords":"Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, Association Learning, Child Psychology, Habituation (Psychophysiology), Probability Theory, Analysis of Variance, Semantics, Symbolism, Behavior, Eye Movements, Macaca mulatta, Prefrontal Cortex, Cats, Dogs, Haplorhini, Photic Stimulation, Electroencephalography, Nervous System Physiology, Darkness, Grasshoppers, Light, Membrane Potentials, Neural Inhibition, Afferent, Picrotoxin, Vision, Deoxyglucose, Injections, Microspheres, Neural Pathways, Rhodamines, Choice Behavior, Speech Perception, Verbal Learning, Dominance, Cerebral, Fixation, Ocular, Language Tests, Random Allocation, Comparative Study, Saguinus, Sound Spectrography, Species Specificity, Audiometry, Auditory Threshold, Calibration, Data Interpretation, Statistical, Anesthesia, General, Electrodes, Implanted, Pitch Perception, Sound Localization, Paired-Associate Learning, Serial Learning, Auditory, Age Factors, Motion Perception, Brain Injuries, Computer Simulation, Blindness, Psychomotor Performance, Color Perception, Signal Detection (Psychology), Judgment, ROC Curve, Regression Analysis, Music, Probability, Arm, Cerebrovascular Disorders, Hemiplegia, Movement, Muscle, Skeletal, Myoclonus, Robotics, Magnetoencephalography, Phonetics, Software, Speech Production Measurement, Epilepsies, Partial, Laterality, Stereotaxic Techniques, Germany, Speech Acoustics, Verbal Behavior, Child Development, Instinct, Brain Stem, Coma, Diagnosis, Differential, Hearing Disorders, Hearing Loss, Central, Neuroma, Acoustic, Dendrites, Down-Regulation, Patch-Clamp Techniques, Wistar, Up-Regulation, Aged, Aphasia, Middle Aged, Cones (Retina), Primates, Retina, Retinal Ganglion Cells, Tympanic Membrane, Cell Communication, Extremities, Biological, Motor Activity, Rana catesbeiana, Spinal Cord, Central Nervous System, Motion, Motor Cortex, Intelligence, Macaca fascicularis, Adoption, Critical Period (Psychology), France, Korea, Magnetic Resonance Imaging, Multilingualism, Auditory Pathways, Cochlear Nerve, Loudness Perception, Neural Conduction, Sensory Thresholds, Sound, Language Disorders, Preschool, Generalization (Psychology), Vocabulary, Biophysics, Nerve Net, Potassium Channels, Sodium Channels, Cues, Differential Threshold, Arousal, Newborn, Sucking Behavior, Ferrets, Microelectrodes, 8459273","bibtex":"@Article{Shamma1993,\n author = {SA Shamma and JW Fleshman and PR Wiser and H Versnel},\n journal = {J Neurophysiol},\n title = {Organization of response areas in ferret primary auditory cortex.},\n year = {1993},\n number = {2},\n pages = {367-83},\n volume = {69},\n abstract = {1. We studied the topographic organization of the response areas obtained\n\tfrom single- and multiunit recordings along the isofrequency planes\n\tof the primary auditory cortex in the barbiturate-anesthetized ferret.\n\t2. Using a two-tone stimulus, we determined the excitatory and inhibitory\n\tportions of the response areas and then parameterized them in terms\n\tof an asymmetry index. The index measures the balance of excitatory\n\tand inhibitory influences around the best frequency (BF). 3. The\n\tsensitivity of responses to the direction of a frequency-modulated\n\t(FM) tone was tested and found to correlate strongly with the asymmetry\n\tindex of the response areas. Specifically, cells with strong inhibition\n\tfrom frequencies above the BF preferred upward sweeps, and those\n\tfrom frequencies below the BF preferred downward sweeps. 4. Responses\n\tto spectrally shaped noise were also consistent with the asymmetry\n\tof the response areas. For instance, cells that were strongly inhibited\n\tby frequencies higher than the BF responded best to stimuli that\n\tcontained least spectral energy above the BF, i.e., stimuli with\n\tthe opposite asymmetry. 5. Columnar organization of the response\n\tarea types was demonstrated in 66 single units from 16 penetrations.\n\tConsistent with this finding, it was also shown that response area\n\tasymmetry measured from recordings of a cluster of cells corresponded\n\tclosely with those measured from its single-unit constituents. Thus,\n\tin a local region, most cells exhibited similar response area types\n\tand other response features, e.g., FM directional sensitivity. 6.\n\tThe distribution of the asymmetry index values along the isofrequency\n\tplanes revealed systematic changes in the symmetry of the response\n\tareas. At the center, response areas with narrow and symmetric inhibitory\n\tsidebands predominated. These gave way to asymmetric inhibition,\n\twith high-frequency inhibition (relative to the BF) becoming more\n\teffective caudally and low-frequency inhibition more effective rostrally.\n\tThese response types tended to cluster along repeated bands that\n\tparalleled the tonotopic axis. 7. Response features that correlated\n\twith the response area types were also mapped along the isofrequency\n\tplanes. Thus, in four animals, a map of FM directional sensitivity\n\twas shown to be superimposed on the response area map. Similarly,\n\tit was demonstrated in six animals that the spectral gradient of\n\tthe most effective noise stimulus varied systematically along the\n\tisofrequency planes. 8. One functional implication of the response\n\tarea organization is that cortical responses encode the locally averaged\n\tgradient of the acoustic spectrum by their differential distribution\n\talong the isofrequency planes. This enhances the representation of\n\tsuch features as the symmetry of spectral peaks and edges and the\n\tspectral envelope.(ABSTRACT TRUNCATED AT 400 WORDS)},\n keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, 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behavior","ferrets","microelectrodes","8459273"],"search_terms":["organization","response","areas","ferret","primary","auditory","cortex","shamma","fleshman","wiser","versnel"],"title":"Organization of response areas in ferret primary auditory cortex.","year":1993}